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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationTue, 02 Dec 2008 12:43:19 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/02/t122824705256r4z3tz4dq92ca.htm/, Retrieved Sat, 25 May 2024 03:17:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28270, Retrieved Sat, 25 May 2024 03:17:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [(Partial) Autocorrelation Function] [nonstationaryques...] [2008-12-01 19:09:36] [922d8ae7bd2fd460a62d9020ccd4931a]
F RMPD    [Cross Correlation Function] [nonstationaryques...] [2008-12-02 17:59:36] [922d8ae7bd2fd460a62d9020ccd4931a]
F   P         [Cross Correlation Function] [nonstationaryques...] [2008-12-02 19:43:19] [89a49ebb3ece8e9a225c7f9f53a14c57] [Current]
F   PD          [Cross Correlation Function] [nonstationaryques...] [2008-12-02 19:52:09] [922d8ae7bd2fd460a62d9020ccd4931a]
Feedback Forum
2008-12-07 10:32:10 [6066575aa30c0611e452e930b1dff53d] [reply] 
Deze moest niet besproken worden aangezien bij de verbetering van Q8 duidelijk is geworden dat we voor d=0 en D=2 niet de kleinste variantie vinden.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
78,4
114,6
113,3
117
99,6
99,4
101,9
115,2
108,5
113,8
121
92,2
90,2
101,5
126,6
93,9
89,8
93,4
101,5
110,4
105,9
108,4
113,9
86,1
69,4
101,2
100,5
98
106,6
90,1
96,9
125,9
112
100
123,9
79,8
83,4
113,6
112,9
104
109,9
99
106,3
128,9
111,1
102,9
130
87
87,5
117,6
103,4
110,8
112,6
102,5
112,4
135,6
105,1
127,7
137
91
90,5
122,4
123,3
124,3
120
118,1
119
142,7
123,6
129,6
151,6
110,4
99,2
130,5
136,2
129,7
128
121,6
135,8
143,8
147,5
136,2
156,6
123,3
100,4
Dataseries Y:
Download CSV
Histogram 
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
127
112,1
114,2
121,1
131,6
125
120,4
117,7
117,5
120,6
127,5
112,3
124,5
115,2
105,4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28270&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28270&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28270&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series2
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series2
krho(Y[t],X[t+k])
-140.00789696035472992
-130.0249149038382450
-12-0.156251779174465
-11-0.220413479285594
-10-0.255679238298054
-9-0.135817475119860
-8-0.091322839982932
-70.00400070857239335
-60.0538943756208137
-50.0229563052417348
-4-0.194671569554522
-30.217643878248291
-2-0.151539776037947
-1-0.248940047584231
00.240315017032304
1-0.00281739904362066
20.0988249841723922
30.303668127768386
40.186184566363325
5-0.0534189630595937
60.0924118082932585
70.0210395974665941
80.181048269050371
9-0.0154141234653996
100.141508507291271
110.0886452636209581
120.0424028932247593
130.120327253213062
140.0538497628612825

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 2 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 2 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & 0.00789696035472992 \tabularnewline
-13 & 0.0249149038382450 \tabularnewline
-12 & -0.156251779174465 \tabularnewline
-11 & -0.220413479285594 \tabularnewline
-10 & -0.255679238298054 \tabularnewline
-9 & -0.135817475119860 \tabularnewline
-8 & -0.091322839982932 \tabularnewline
-7 & 0.00400070857239335 \tabularnewline
-6 & 0.0538943756208137 \tabularnewline
-5 & 0.0229563052417348 \tabularnewline
-4 & -0.194671569554522 \tabularnewline
-3 & 0.217643878248291 \tabularnewline
-2 & -0.151539776037947 \tabularnewline
-1 & -0.248940047584231 \tabularnewline
0 & 0.240315017032304 \tabularnewline
1 & -0.00281739904362066 \tabularnewline
2 & 0.0988249841723922 \tabularnewline
3 & 0.303668127768386 \tabularnewline
4 & 0.186184566363325 \tabularnewline
5 & -0.0534189630595937 \tabularnewline
6 & 0.0924118082932585 \tabularnewline
7 & 0.0210395974665941 \tabularnewline
8 & 0.181048269050371 \tabularnewline
9 & -0.0154141234653996 \tabularnewline
10 & 0.141508507291271 \tabularnewline
11 & 0.0886452636209581 \tabularnewline
12 & 0.0424028932247593 \tabularnewline
13 & 0.120327253213062 \tabularnewline
14 & 0.0538497628612825 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28270&T=1

[TABLE]
[ROW][C]Cross Correlation Function[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of X series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]2[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]2[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]0.00789696035472992[/C][/ROW]
[ROW][C]-13[/C][C]0.0249149038382450[/C][/ROW]
[ROW][C]-12[/C][C]-0.156251779174465[/C][/ROW]
[ROW][C]-11[/C][C]-0.220413479285594[/C][/ROW]
[ROW][C]-10[/C][C]-0.255679238298054[/C][/ROW]
[ROW][C]-9[/C][C]-0.135817475119860[/C][/ROW]
[ROW][C]-8[/C][C]-0.091322839982932[/C][/ROW]
[ROW][C]-7[/C][C]0.00400070857239335[/C][/ROW]
[ROW][C]-6[/C][C]0.0538943756208137[/C][/ROW]
[ROW][C]-5[/C][C]0.0229563052417348[/C][/ROW]
[ROW][C]-4[/C][C]-0.194671569554522[/C][/ROW]
[ROW][C]-3[/C][C]0.217643878248291[/C][/ROW]
[ROW][C]-2[/C][C]-0.151539776037947[/C][/ROW]
[ROW][C]-1[/C][C]-0.248940047584231[/C][/ROW]
[ROW][C]0[/C][C]0.240315017032304[/C][/ROW]
[ROW][C]1[/C][C]-0.00281739904362066[/C][/ROW]
[ROW][C]2[/C][C]0.0988249841723922[/C][/ROW]
[ROW][C]3[/C][C]0.303668127768386[/C][/ROW]
[ROW][C]4[/C][C]0.186184566363325[/C][/ROW]
[ROW][C]5[/C][C]-0.0534189630595937[/C][/ROW]
[ROW][C]6[/C][C]0.0924118082932585[/C][/ROW]
[ROW][C]7[/C][C]0.0210395974665941[/C][/ROW]
[ROW][C]8[/C][C]0.181048269050371[/C][/ROW]
[ROW][C]9[/C][C]-0.0154141234653996[/C][/ROW]
[ROW][C]10[/C][C]0.141508507291271[/C][/ROW]
[ROW][C]11[/C][C]0.0886452636209581[/C][/ROW]
[ROW][C]12[/C][C]0.0424028932247593[/C][/ROW]
[ROW][C]13[/C][C]0.120327253213062[/C][/ROW]
[ROW][C]14[/C][C]0.0538497628612825[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28270&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28270&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series2
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series2
krho(Y[t],X[t+k])
-140.00789696035472992
-130.0249149038382450
-12-0.156251779174465
-11-0.220413479285594
-10-0.255679238298054
-9-0.135817475119860
-8-0.091322839982932
-70.00400070857239335
-60.0538943756208137
-50.0229563052417348
-4-0.194671569554522
-30.217643878248291
-2-0.151539776037947
-1-0.248940047584231
00.240315017032304
1-0.00281739904362066
20.0988249841723922
30.303668127768386
40.186184566363325
5-0.0534189630595937
60.0924118082932585
70.0210395974665941
80.181048269050371
9-0.0154141234653996
100.141508507291271
110.0886452636209581
120.0424028932247593
130.120327253213062
140.0538497628612825


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 2 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 2 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 2 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 2 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par5 == 0) {
y <- log(y)
} else {
y <- (y ^ par5 - 1) / par5
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par6 > 0) y <- diff(y,lag=1,difference=par6)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
if (par7 > 0) y <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',ylab='CCF',xlab='Lag (k)'))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Cross Correlation Function',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of X series',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of X series',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of X series',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of Y series',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of Y series',header=TRUE)
a<-table.element(a,par6)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of Y series',header=TRUE)
a<-table.element(a,par7)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'k',header=TRUE)
a<-table.element(a,'rho(Y[t],X[t+k])',header=TRUE)
a<-table.row.end(a)
mylength <- length(r$acf)
myhalf <- floor((mylength-1)/2)
for (i in 1:mylength) {
a<-table.row.start(a)
a<-table.element(a,i-myhalf-1,header=TRUE)
a<-table.element(a,r$acf[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')